The use of computing systems has increased to provide useful services for many facets of users' business and everyday life. Nevertheless, malicious users seem to continually attempt to gain access to other's computing systems for illicit (i.e., unauthorized) purposes, such as spying or other vandalous or nefarious activities. These malicious users launch attacks against computer systems, often exploiting weaknesses to gain entry. They have implemented numerous types of malicious software which may be collectively referred to as “malware.” Malware generally refers to any software used to spy on a target computing system, or otherwise cause harm to the target computing system, such as intentional corruption of data stored on the computing system, theft of intellectual property, theft of credit card information, identity theft, bank fund transfer fraud, and the like. Examples of malware may include, for example, viruses, trojan horses, worms, and/or other programs intended to compromise computing systems as well as the data stored on these computing systems.
Many network devices within enterprises are monitored for purposes of security with a view to identifying indicators of compromise (IOCs) evidencing, verifying or tracking a malicious attack. The attack may be conducted by a human perpetrator such as a hacker or by malware. The resulting data can be presented to network or security administrators for their review, evaluation and, if appropriate, remedial action. Since this process can be challenging, various tools have been created to aid in finding “data of interest” within the presented logs.
It is known to use a Security Information and Event Manager (SIEM) to aggregate data related to security-related “events” (run-time behaviors) from multiple network devices. An SIEM can provide a holistic view of an organization's information technology (IT) security. Relevant data about IT security is typically produced in multiple locations (e.g., different network devices) and the SIEM aggregates the data to allow a single point of view to detect trends and patterns that may represent IOCs of IT security.
Known SIEMs may accomplish such aggregation by deploying multiple collection agents. These are installed in network devices (e.g., notebooks, servers, firewalls, routers, and/or intrusion protection systems) to gather the event data from their respective devices and store the event data in event logs maintained by the devices. Using the collection agents, the collected event data are supplied to a centralized management console, which stores them in a repository for purposes of analysis typically by trained security personnel, and provides reports for compliance assessment and remediation. The management console may also detect anomalies in the collected data, but to accomplish this, a highly trained SIEM administrator must typically first undertake the laborious task of developing a profile of the network devices and environment under normal operating conditions.
A drawback of such systems is that the volume of information being aggregated can be so large as to render extraction of actionable intelligence regarding IT security impractical. Also, SIEMs are typically expensive to deploy, complex to operate and manage, produce a high level of false positives and false negatives, and require highly trained personnel.